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Hi all, Here I include an RFC for control flow sensitive AutoFDO (FS-AFDO). This is a joint work with David Li. Questions and feedback are welcome. Thanks, Rong ============= [RFC] Control Flow Sensitive AutoFDO (FS-AFDO) 1. Motivation AFDO profile is derived from PMU samples from running an earlier build binary. PMU samples are indexed by the IP addresses. An offl...

...Id". +Hongtao as well. Thanks, Wenlei From: llvm-dev <llvm-dev-bounces at lists.llvm.org> Date: Tuesday, November 17, 2020 at 9:55 AM To: llvm-dev <llvm-dev at lists.llvm.org> Cc: David Li <davidxl at google.com> Subject: [llvm-dev] [RFC] Control Flow Sensitive AutoFDO (FS-AFDO) Hi all, Here I include an RFC for control flow sensitive AutoFDO (FS-AFDO). This is a joint work with David Li. Questions and feedback are welcome. Thanks, Rong ============= [RFC] Control Flow Sensitive AutoFDO (FS-AFDO) 1. Motivation AFDO profile is derived from PMU samples from run...

...t CSSPGO. > > > > [hongtao] By flow-sensitivity, do you mean the execution trace of blocks > in a function? > More like the path sensitive profile -- a realistic way of getting that is from post cfg transformation profiles. Rong is going to share a proposal based on the current AFDO implementation. > This is missing from CSSPGO currently. Pseudo probe can be viewed as a > cost-free instrumentation technique that correlates hardware samples to the > IR for sample profiling. It may never achieve the precision of real > instrumentation. It is currently combined with...

...r pseudo-probe to work without CSSPGO. [hongtao] By flow-sensitivity, do you mean the execution trace of blocks in a function? More like the path sensitive profile -- a realistic way of getting that is from post cfg transformation profiles. Rong is going to share a proposal based on the current AFDO implementation. [wenlei] How significant flow-sensitivity is comparing to context-sensitivity? Looking forward to the proposal, and wondering if it can be combined with CSSPGO and pseudo-probe. [hongtao] Great, looking forward to Rong’s proposal. This is missing from CSSPGO currently. Pseudo prob...

Is there prior art for this sort of thing (in GCC, for example) - I take it this isn't the first time this has come up as a problem for profile accuracy? (so it'd be helpful to know prior solutions to this (& if we're not doing whatever was done before, what it is about our situation that's different, etc), or why it hasn't been a problem, etc) On Thu, Oct 27, 2016 at

...ay freeze only to find surprising perf regression due to AutoFDO 😊. It also opens up possibility of fuzzy CFG matching when there’s a CFG mutation due to source change to make it even more resilient. Ok. Also see my reply above. It seems to me that the line shifting problem should be solvable for AFDO (or make it more tolerant). [wenlei] Agreed that we can do better with line number approach too. But CFG as profile carrier has richer info than line, and is closer to profile which is inherently CFG based. So I think it should be easier with probe and CFG. New profile format and profile gener...

The profile summary is saved in the global metadata ASAIK. If we want to calculate if something is hot/cold while choosing functions for importing, we would either need to read whole Module (which we clearly don't want to do) or duplicate this information in the summary, so we could get it without reading Module. 2016-09-02 15:49 GMT-07:00 Mehdi Amini <mehdi.amini at apple.com>: >

...ay freeze only to find surprising perf regression due to AutoFDO 😊. It also opens up possibility of fuzzy CFG matching when there’s a CFG mutation due to source change to make it even more resilient. Ok. Also see my reply above. It seems to me that the line shifting problem should be solvable for AFDO (or make it more tolerant). [wenlei] Agreed that we can do better with line number approach too. But CFG as profile carrier has richer info than line, and is closer to profile which is inherently CFG based. So I think it should be easier with probe and CFG. New profile format and profile gener...

...ay freeze only to find surprising perf regression due to AutoFDO 😊. It also opens up possibility of fuzzy CFG matching when there’s a CFG mutation due to source change to make it even more resilient. Ok. Also see my reply above. It seems to me that the line shifting problem should be solvable for AFDO (or make it more tolerant). [wenlei] Agreed that we can do better with line number approach too. But CFG as profile carrier has richer info than line, and is closer to profile which is inherently CFG based. So I think it should be easier with probe and CFG. New profile format and profile gener...

Dear experts, I?ve been on this for weeks now, and couldn?t find a solution..Sorry for the long description. I figured I post many details, so you get the problem entirely, although it?s not hard to grasp. **Situation:** Data frame consisting of 4 million entries (total size: 250 MB). Two columns: `ID` and `TEXT`. Text strings are each up to 200 characters. **Task:** Preprocessing the text

Thanks for the thoughtful questions, David. See my answers inline. Thanks, Wenlei From: Xinliang David Li <davidxl at google.com> Date: Friday, August 7, 2020 at 1:24 PM To: Wenlei He <wenlei at fb.com> Cc: "llvm-dev at lists.llvm.org" <llvm-dev at lists.llvm.org>, Wei Mi <wmi at google.com>, Hongtao Yu <hoy at fb.com> Subject: Re: [RFC] Context-sensitive

Motivation: Many optimizations duplicate code. E.g. loop unroller duplicates the loop body, GVN duplicates computation, etc. The duplicated code will share the same debug info with the original code. For SamplePGO, the debug info is used to present the profile. Code duplication will affect profile accuracy. Taking loop unrolling for example: #1 foo(); #2 for (i = 0; i < N; i++) { #3 bar();

Hi All, Our team at Facebook is building a new context-sensitive Sample PGO as an alternative to the existing AutoFDO. We’d like to share our motivation, propose a new design, and reveal preliminary results on benchmarks. We will refer to the proposed design as CSSPGO in this RFC. The new CSSPGO leverages simultaneous LBR and stack sampling to construct a full context-sensitive profile. It